For what it's worth, github search only finds two instances of this usage: https://github.com/search?q=%22np.dtype%28np.floating%29%22&type=Code
On Fri, Feb 14, 2020 at 2:28 PM Sebastian Berg <sebast...@sipsolutions.net> wrote: > Hi all, > > In https://github.com/numpy/numpy/pull/15534 I would like to start > deprecating creating dtypes from "abstract" scalar classes, such as: > > np.dtype(np.floating) is np.dtype(np.float64) > > While, at the same time, `isinstance(np.float32, np.floating)` is true. > > Right now `arr.astype(np.floating, copy=False)` and, more obviously, > `arr.astype(np.dtype(np.floating), copy=False)` will cast a float32 > array to float64. > > I think we should deprecate this, to consistently enable that in the > future `dtype=np.floating` may choose to not cast a float32 array. Of > course for the `astype` call the DeprecationWarning would be changed to > a FutureWarning before we change the result value. > > A slight (but hopefully rare) annoyance is that `np.integer` might be > used since it reads fairly well compared to `np.int_`. The large > upstream packages such as SciPy or astropy seem to be clean in this > regard, though (at least almost clean). > > Does anyone think this is a bad idea? To me these deprecations seem > fairly straight forward, possibly flush out bugs/unintended behaviour, > and necessary for consistent future behaviour. (More similar ones may > have to follow). > > If there is some, but not much, hesitation, I can also add this to the > NEP 41 draft. Although I currently feel it is the right thing to do > even if we never had any new dtypes. > > - Sebastian > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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